package association;

import java.io.File;

import javax.imageio.ImageIO;

import descriptors.HoG;
import parameters.tracking_arguments;
import particlefiltering.observation;
import particlefiltering.pHistogram;
import tracking.Atributes;

public class Probabilities {
	
	
	public double prob_app (Atributes A1, Atributes A2, tracking_arguments tracking_parameters, int frame, int boxi, int boxj, String image_name)
	{
		/*Consertar os parametros aqui*/
		
		/*try {
			ImageIO.write(A1.image, "png", new File("./comparado/"+image_name+"_"+String.format("%02d", boxi)+"_"+String.format("%02d", boxj)+".A1.png"));
			//ImageIO.write(Original, "png", new File(out_path + String.format("%05d", iframe) + "/detection.png"));
		}
		catch (Exception e) {
			System.err.println("cannot store image");
		}
		
		try {
			ImageIO.write(A2.image, "png", new File("./comparado/"+image_name+"_"+String.format("%02d", boxi)+"_"+String.format("%02d", boxj)+".A2.png"));
			//ImageIO.write(Original, "png", new File(out_path + String.format("%05d", iframe) + "/detection.png"));
		}
		catch (Exception e) {
			System.err.println("cannot store image");
		}*/
		
		pHistogram histo1 = new pHistogram();
		HoG hog1 = new HoG();
		//double[] e1 = hog1.HoGFixedNumberOfCells (A1.image, tracking_parameters.numCellsX, tracking_parameters.numCellsY, tracking_parameters.blockSize);
		//double[] e1 = hog1.HoGFixedNumberOfCells (A1.image, 2, 2, 2);
		double[] e1 = hog1.hog(A1.image, 5, 1, 1, 9, 32, false);
		histo1.alloc_vector(e1.length);
		for (int i = 0; i < e1.length; i++) {
		  histo1.set_data(i, e1[i]);
		}
		
		observation obs = new observation();
		
		obs.normalize_histogram(histo1);
		
		pHistogram histo2 = new pHistogram();
		HoG hog2 = new HoG();
		//double[] e2 = hog2.HoGFixedNumberOfCells (A2.image, tracking_parameters.numCellsX, tracking_parameters.numCellsY, tracking_parameters.blockSize );
		//double[] e2 = hog2.HoGFixedNumberOfCells (A2.image, 2, 2, 2);
		double[] e2 = hog1.hog(A2.image, 5, 1, 1, 9, 32, false);
		histo2.alloc_vector(e2.length);
		for (int i = 0; i < e2.length; i++) {
		  histo2.set_data(i, e2[i]);
		}
	
		obs.normalize_histogram(histo2);

		/* compute likelihood as e^{\lambda D^2(h, h^*)} */
		double d_sq = obs.histo_dist_sq (histo1, histo2);

		return Math.exp (-tracking_parameters.sigma_app * d_sq);
	}
	
	public double prob_pos (Atributes A1, Atributes A2, tracking_arguments tracking_parameters)
	{
	
		double d = Math.sqrt ( 
				( A2.get_x() - A1.get_x() ) * ( A2.get_x() - A1.get_x() ) + 
				( A2.get_y() - A1.get_y() ) * ( A2.get_y() - A1.get_y() ) );

	    double sigma = tracking_parameters.sigma_pos; 
	    
	    double prob = Math.exp (-(d*d)/(2*sigma*sigma));

	    return prob;
	}
	
	public double prob_size (Atributes A1, Atributes A2, tracking_arguments tracking_parameters)
	{
		//double s = Math.max(s1, s2)/Math.min(s1,s2);
		int s1 = A1.get_width() * A1.get_height();
		
		int s2 = A2.get_width() * A2.get_height();
		
		double s = (s1-s2)/s1;
		
		double sigma = tracking_parameters.sigma_size;
	    
	    double prob = Math.exp (-(s*s)/(2*sigma*sigma));

	    return prob;
	}
	
	
		
	   
}